We specialize in helping our clients design and implement dimensional data warehouses and data marts using the Ralph Kimball star schema approach on MySQL databases using Infobright, which includes its query optimizer and Brighthouse storage engine.

We also migrate data warehouse and data mart presentation areas and reporting and analytical databases to Infobright from row-oriented databases, as well as creating Infobright databases of machine-generated data.

We recommend using an agile, iterative approach to development. This provides useful functionality quickly, helps obtain periodic business user feedback, and helps keep the project from going off track.

We follow Ralph Kimball's 25 Best Practices for Big Data.

Our services

• Proof of concept or pilot of dimensional data warehouse or data mart on Infobright.
• Migration of data warehouse or data mart presentation area or analytical or reporting database to Infobright from a row-oriented database, such as Oracle, IBM DB2, Microsoft SQL Server, and Sybase ASE.
• Creation of an Infobright database of machine-generated data.
• Leading, or assisting in, the design and implementation of a dimensional data warehouse or data mart on Infobright.

Our fees

Our services are available on a contingency fee, fee per hour, fee per service, or customized basis. Click on Fees for more information.

• Curt Monash concluded, December 2, 2012, "Column stores will almost always have a compression and/or compression performance advantage over row stores."

  Samara Lynn reported, September 19, 2012, at PCMag.com, "Because less data is returned when searching against a columnar database, analytics and searches can be performed much faster than with row databases."

The June 2, 2012 Information Management slideshow said "Column-oriented ... database ... is conducive to performing many selective queries rapidly, a benchmark of big data analytics."

Boris Evelson, VP and Principal Analyst of Forrester Research, wrote May 30, 2011, "fitting BI into a row-oriented RDBMS is often like putting a square peg into a round hole."

David Menninger, VP and Research Director of Ventana Research, wrote March 3, 2011: "Fundamentally, columnar database technology offers two primary benefits increased speed and reduced storage requirements. We repeatedly emphasize the importance of speed to end users."

Doug Henschen reported in InformationWeek, January 27, 2011, "the performance efficiencies of columnar querying are unmatched by any row-oriented database."

The Bloor Research November 2010 white paper "What's Cool about Columns [and how extend their benefits]" concluded, on page 15:

"Columns provide better performance at a lower cost with a smaller footprint: it is difficult to understand why any company seriously interested in query performance would not consider a column-based solution.

Using columns instead of rows means that you get greatly reduced I/O because you only read the columns referenced by the query. This means that you get dramatically improved performance. The use of compression improves I/O rates (and performance) still further."

Seth Grimes reported in InformationWeek, November 16, 2010, "Column-oriented stores can accelerate many analytical queries, dramatically reduce disk I/O, and slash storage requirement via aggressive compression."

Intelligent Enterprise reported February 22, 2010, "Column-store databases are typically faster than conventional, row-oriented databases (such as Oracle, IBM DB2 and Microsoft SQL Server) in analytic applications because they can query specific data attributes in columns -- such as zip codes, product stock numbers or transaction totals -- while skipping all the other data, row-by-row, that might not be relevant to a query."

Information Management Online reported February 15, 2010, "IDC ... predicts five-year horizon will shift data warehousing to columnar...."

Infobright "Column vs Row" 3 minute web cast.